This hands-on course guides you through leveraging Azure Machine Learning to streamline model development. Discover how to automate classification model selection using AutoML (Python SDK v2) and implement effective experiment tracking with MLflow in Jupyter notebooks. Designed for data scientists, it combines automated workflows with practical notebook experimentation to optimize ML pipelines.

This ​​5.5-hour Microsoft Learn course​​ equips cybersecurity professionals with AI-driven skills to transform security operations using ​​Microsoft Security Copilot​​. Designed for analysts and IT administrators, it covers generative AI fundamentals, Security Copilot's core capabilities (plugins, promptbooks, threat intelligence integration), and hands-on use cases for threat hunting, incident response, and compliance management. The course bridges theoretical AI concepts with practical workflows, emphasizing integration with Microsoft Defender XDR, Sentinel, and Intune.

This 6-hour, 24-minute course teaches you to unlock insights from structured and unstructured data using ​​Azure AI Search​​. Over eight modules, you'll learn to build intelligent search solutions, create custom AI skills, manage knowledge stores, implement advanced search features, and integrate external data sources. Designed for developers and AI engineers, the course combines hands-on exercises with practical strategies for optimizing search performance, semantic reranking, and vector-based retrieval—empowering you to transform raw data into actionable intelligence.

This 2-hour 37-minute Azure Machine Learning course teaches professionals to optimize model training through four comprehensive modules. Learners will master script conversion to command jobs, MLflow metric tracking, hyperparameter tuning via sweep jobs, and pipeline automation using components. Designed for cloud-based ML workflows, it combines hands-on exercises with practical implementation strategies for enterprise-grade machine learning operations.

This 3-hour 37-minute Azure Machine Learning course provides a comprehensive exploration of workspace configuration and management. Through 5 hands-on modules, learners will master workspace creation, developer tool integration (Studio, Python SDK, CLI), data asset management, compute resource optimization, and environment configuration. Designed for data professionals, it combines theoretical concepts with practical exercises for deploying scalable ML workloads in Azure.

This 1-hour 35-minute Microsoft Learn path empowers nonprofit professionals to harness AI efficiency through Microsoft 365 Copilot. Spanning 3 practical modules, learners discover how to craft effective prompts across Word, Outlook, PowerPoint, Excel, and Teams. Designed specifically for nonprofit workflows, the course combines ethical AI principles with hands-on document drafting, email automation, and collaborative productivity enhancements.

This 2-hour 18-minute learning path equips IT professionals and developers with advanced strategies to customize Microsoft 365 Copilot for organizational needs. Through 3 technical modules, learners explore extensibility fundamentals, development path selection, and administrative management of agents, connectors, and plugins. Designed for enterprise teams, it combines AI orchestration concepts with practical guidance on integrating business data and automating workflows.

This 2-hour 7-minute learning path democratizes AI for non-technical business professionals through Microsoft's Power Platform ecosystem. Focused on ​​Power BI​​ and ​​Power Platform​​, it teaches how to create AI-powered dashboards, automate workflows, and generate actionable insights without coding. Designed for managers and operational staff, the course bridges the gap between data science teams and business units by demonstrating practical AI implementation in reporting (Module 1) and process automation (Module 2).

This 4-hour 28-minute technical learning path empowers developers to build next-generation AI agents using Azure's cutting-edge tools. Through 5 hands-on modules, engineers will master AI agent development using ​​Azure AI Agent Service​​ and ​​Semantic Kernel Framework​​. From foundational concepts to multi-agent orchestration, the course covers custom tool integration, plugin development, and collaborative agent systems. Designed for cloud developers and AI practitioners, it combines theory with practical exercises for enterprise-grade AI solutions.

This 2-hour 26-minute learning path empowers Teams users to create custom solutions using Microsoft's low-code ecosystem. Through 5 practical modules, learners master app development (Power Apps), workflow automation (Power Automate), AI agent creation (Copilot Studio), and data reporting (Power BI) within Microsoft Teams. Designed for business users and IT teams, it combines Dataverse for Teams' governance capabilities with hands-on exercises to build enterprise-ready solutions without coding expertise.